Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
SQL Server 2016 Developer's Guide

You're reading from   SQL Server 2016 Developer's Guide Build efficient database applications for your organization with SQL Server 2016

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786465344
Length 616 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
Miloš Radivojević Miloš Radivojević
Author Profile Icon Miloš Radivojević
Miloš Radivojević
William Durkin William Durkin
Author Profile Icon William Durkin
William Durkin
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to SQL Server 2016 2. Review of SQL Server Features for Developers FREE CHAPTER 3. SQL Server Tools 4. Transact-SQL Enhancements 5. JSON Support in SQL Server 6. Stretch Database 7. Temporal Tables 8. Tightening the Security 9. Query Store 10. Columnstore Indexes 11. Introducing SQL Server In-Memory OLTP 12. In-Memory OLTP Improvements in SQL Server 2016 13. Supporting R in SQL Server 14. Data Exploration and Predictive Modeling with R in SQL Server

Nonclustered columnstore indexes

After all of the theoretical introduction, it is time to start using the columnar storage. You will start by learning how to create and use nonclustered columnstore indexes (NCCI). You already know from the previous section that a NCCI can be filtered. Now you will learn how to create, use, and ignore a NCCI. In addition, you will measure the compression rate of the columnar storage.

Because of the different burdens on SQL Server when a transactional application uses it compared to analytical applications usage, traditionally, companies split these applications and created data warehouses. Analytical queries are diverted to the data warehouse database. This means that you have a copy of data in your data warehouse, of course with a different schema. You also need to implement the Extract Transform Load (ETL) process for scheduled loading of the data warehouse. This means that the data you analyze is somehow stall. Frequently, the data is loaded overnight...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image